Innovation

When I teach about Crowdsourcing and Open Innovation in my Social Dynamics course at Kellogg we look at a ton of examples of how innovative organizations are using these tools to connect with a global network of problem solvers, innovators, and regular people to make more accurate predictions, find better problem solutions, and speed the pace of innovation. One of my students recently suggested that I compile a list of these examples so that the class could have all of the links in one place. So, here is a roughly annotated list of some of my favorite examples. Some of these are platforms you can use and others are organizations that are using or have used crowds in innovative ways. If you have others, I would love to hear about them.

Processing unstructured data

Many organizations today have more data than they know what to do with. Much of this data is what we call “unstructured” — it’s not a nice spreadsheet that we can feed into a regression or even in to a fancy machine learning algorithm. Instead the data is in the form of images or massive amounts of text that we don’t really know how to handle. Crowdsourcing has proven to be a very effective way to process this kind of unstructured data into something usable.

The New York Times asked to crowd to help comb through the thousands of pages of Sarah Palin’s email released by court order and flag newsworthy content. Then the professional editors would take a closer look at flagged items and do the background research to put together a real new story.

You know those online security questions where you have to enter some fuzzy text or a blurry number? Sometimes you are actually helping to process scanned text that was too muddled for a computer to read.

Duolingo is an awesome FREE language learning app. It’s secret to staying free is that while people are using the app to learn a language, Duolingo makes money from the documents that they translate. Started by the same people that came up with reCaptcha.

This is an academic study that used crowdsourcing to help form a rating system for how much an image has been digitally altered. Outstanding example of how crowds can be used to “train computers” to process unstructured data.

Expert tasks that are inefficient to bring in house

Often times we have jobs to be done where we could really use a little bit of an expert, but we don’t really need a whole employee. After all, hiring people is expensive. Any time you hire someone it costs money to find them, you have to give them a desk, and a phone, and a computer, and benefits, and usually you’re stuck with them for a while. Sometimes it would be nice to have just a part of an employee - say, 1/4 of a marketer, 1/10 of a graphic designer, 1/10 of a web designer, and 1/3 of a data scientist. Crowdsourcing effectively lets you do this.

Have an idea for a great product? Submit it on Quirky. Used by companies like Bed, Bath, and Beyond, Target, Toys R Us, and Ace Hardware.

Crowdfunding

Crowdfunding allows us to distribute the risk of funding new projects across a huge number of people. It’s also a great way of using a “Measure and React Strategy” because in many cases, like on Kickstarter, people effectively commit to buy your product before you have to take the risk of producing it.

The most prominent crowdfunding platform on the Web, Kickstarted started to fund arts projects but has grown to much, much more, raising millions of dollars in startup capital for projects like the Pebble smart watch.

Open innovation

One of the most powerful uses of the crowd is through open innovation platforms. This application is designed to take advantage of the super additive benefits of diversity. For more on how the power of diversity leads to better problem solving, I highly recommend Scott E. Page’s book The Difference, which was once aptly described as “an airplane book if you’re on a flight to Singapore."

The largest, most developed open innovation platform hosts challenges of all sorts, but especially problems in chemistry and engineering. Prizes for solutions often extended into the tens of thousands.

Amazon Mechanical Turk is a platform for all of the above. The most developed and effective crowdsourcing platform on the web, with a massive population of workers (aka Turkers), Mechanical Turk can be used for processing data, running experiments, disseminating surveys, … you name it.

In Google's first issue of "Think Quarterly," it's new business to business publication, Susan Wojcicki, Google's employee number 16, sums up the classic exploration versus exploitation tradeoff writing, "We face the classic innovator’s dilemma: should we invest in brand new products, or should we improve existing ones?"

James March laid out this ubiquitous dilemma, which every organization faces in one form or another, in his now classic paper, "Exploration and Exploitation in Organizational Learning." Each summer at the University of Michigan's ICPSR Summer Program on Quantitative Methods I co-teach a course on complex systems models in the social sciences in which I often discuss March's famous paper (in fact, we just discussed the paper today). In going over the paper this summer I was struck again by the continuing relevance of his insights.

The quote that grabbed me today was, "... adaptive processes characteristically improve exploitation more rapidly than exploration ... these tendencies to o increase exploitation and reduce exploration make adaptive processes potentially self-destructive." Here, March says we have to constantly be on guard to preserve exploration in our organizations. Our natural tendency, just by doing what's best for us in the short run, is to gradually scale back exploration in favor exploitation, until all we do is exploit. But, in doing so, we ultimately doom our organization to failure because we're no longer able to adapt to changing environment, or we lock into a sub optimal solution and eventually our competitors surpass us (see the earlier post on Borders). March issued this warning to all organizations long before Clayton Christensen's Innovator's Dilemma. The process of adaptation that makes us good at what we do now will destroy us down the road if we don't actively work to preserve exploration in our organization. Which brings us back to Google. Google is famous for so-called "20 percent time" in which engineers are asked to dedicate a full day a week to things "not necessarily in their job description." This is Google's way of actively maintaining exploration in their organization. So far, it seems to be working for them.

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About the Blog

This is a blog about social interactions. When people interact and influence one another's choices, the resulting macro level dynamics can be complex, astounding, horrific, and/or beautiful. In my research, I use modeling to try and understand how social interactions give rise to this astounding diversity of phenomena. The blog is a place for me to make more casual observations about social dynamics in the news, in my research, in other people's research, and in everyday life.